The study investigates the combined influence of pedagogical adaptability, student engagement, quality management strategies, teacher support, technological integration, assessment and feedback, and parental involvement on students’ learning outcomes at the higher-secondary level. Using a quantitative, cross-sectional design and Structural Equation Modelling (SEM) with 290 respondents, the analysis revealed that student engagement, technological integration, quality management, and parental involvement significantly enhance learning outcomes, while teacher support, pedagogical adaptability, and assessment and feedback were not statistically significant. The model demonstrated good fit indices (χ²/df = 1.294, GFI = 0.900). Findings highlight the importance of engagement, technology, and parental collaboration in improving educational effectiveness..

This study investigates how adaptive teaching, technological integration, curriculum strategies, assessment and innovation, professional development, student engagement, and educational change influence teachers’ professional competencies in secondary schools. Using a quantitative survey design and structural equation modelling (SEM) on data from 260 teachers, the research identifies technological integration, curriculum strategies, student engagement, and educational change as significant predictors of professional competence. Findings highlight gaps in assessment practices and interdisciplinary approaches but underscore the need for modernized, engagement-driven pedagogy. Results provide actionable insights for policymakers and educators to enhance teacher effectiveness through targeted professional growth and systemic educational reforms..

This study examines how psychological, behavioural, and environmental factors shape students’ ability to manage time effectively in higher education. Using a quantitative design and Structural Equation Modelling (SEM) on responses from 255 students in Jharkhand and Bihar, the study tests the influence of self-motivation, academic stress, goal orientation, technological support, parental participation, student engagement, and personal skills on time management and study techniques. Results indicate that personal skills, parental participation, and goal orientation are strong positive predictors of effective planning, scheduling, and task completion. The findings provide an evidence base for interventions such as skills training, parental academic involvement, and goal-setting support to improve self-regulated learning..

This study presents the design, modeling, and experimental validation of novel hybrid cooling technologies for high-power electronic systems, integrating nanofluid-based forced convection with phase-change material (PCM) latent heat absorption. The research aims to overcome the limitations of conventional air and liquid cooling systems by improving heat dissipation, energy efficiency, and thermal stability under variable power loads. Experimental investigations, supported by MATLAB R2017b, ANSYS Fluent, and COMSOL Multiphysics simulations, were conducted for heat loads ranging from 50 W to 300 W. Results indicate that the hybrid nanofluid–PCM system achieved a minimum thermal resistance of 0.28 K/W, an average heat transfer coefficient of 550 W/m²·K, and a Coefficient of Performance (COP) between 5.8 and 8.8, significantly outperforming air and liquid cooling alternatives..

India is a country that possesses enormous resources, which has attracted a vast number of countries to put those riches to use and enrich their economies to the fullest extent possible. Customers' tastes and preferences are also subject to rapid change in today's environment, which is characterized by the rapid advancement of technology. For the sake of India's overall growth and for the purpose of achieving economic autonomy among its population, it is essential that rural areas experience rapid industrialization. The role of the small-scale industries is to assist in the expansion of the government's infrastructure and to reduce problems such as pollution, poverty, and slums..

Mathematical disciplines that study spaces where distances between points may be measured include metric space theory and metric geometry. These theories lay out a rigorous framework for studying the shapes, sizes, and relationships of things in real and virtual worlds. Geometric and analytical concepts may be applied to large regions by starting with the basic concept of a metric, which is a function that defines the distance between points. .

The exponential growth of online social networks (OSNs) has dramatically altered the ways in which people communicate, share information, and engage with one another. Concerns about data privacy, unauthorized access, and user monitoring have grown in tandem with the use of this link. This research introduces a new paradigm for community key management in online social networks (OSNs) that prioritizes privacy..

This study presents a sentiment analysis model for classifying user-generated drug reviews into positive, neutral, and negative categories using transformer-based embeddings and hybrid classifiers. A dataset of 5,170 drug reviews was collected from WebMD using the Beautiful Soup Python library and manually labeled for accuracy. After preprocessing and encoding, embeddings were generated using BERT, SciBERT, BioBERT, and SBERT models to capture contextual meaning. These embeddings were then used as input features for machine learning classifiers such as Decision Tree, Support Vector Machine (SVC), Random Forest, and Recurrent Neural Network (RNN). Experiments were conducted using Python (v3.9.11) and the SMOTE technique to address class imbalance. .

A fresh look at the geometric underpinnings of Einstein's Special and General Relativity has been driven by the ongoing conceptual difficulties with these theories, including simultaneity, curvature of spacetime, time dilation, and length contraction. For the purpose of addressing the Minkowskian model's inherent inconsistencies and interpretational challenges, this research suggests a Euclidean framework as an alternate formulation. This work shows that one need not invoke non-Euclidean spacetime curvature in order for relativistic effects to arise naturally from geometric relations by reinstating absolute Euclidean space and genuine temporal progression. .

This study examines IPO underpricing and long-term performance in the Indian capital market by analysing investor perceptions and key determinants influencing IPO pricing behaviour. Using primary data collected from 450 respondents and supported by structural equation modelling, the study finds that IPO underpricing is a widely perceived and systematic feature of the Indian market. Listing-day gains are viewed as clear evidence of underpricing and are found to benefit short-term investors more than long-term investors. Firm size, firm age, issue size, subscription rate, and market conditions significantly influence IPO pricing outcomes, while market volatility and underwriter reputation exert limited direct impact. The findings suggest that IPO underpricing in India is driven largely by investor psychology, demand management, and favourable market sentiment rather than pure pricing inefficiency. The study provides insights for investors, issuers, and regulators seeking to enhance IPO pricing efficiency and market transparency..